Data Visualisation - Europe Energy Production

Introduction

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Libraries

library(tidyverse)
library(httr)
library(readxl)
library(plotly)

Preprocessing

Import

# embed code from https://data.world/makeovermonday/2021w5
GET("https://query.data.world/s/rnsywm4k4ae3vz2iitu6cg4sww6xbc", 
    write_disk(tf <- tempfile(fileext = ".xlsx")))
raw <- read_excel(tf)

Refactor columns

data <- raw %>%
  select(Year = Year, Country = Area, Source = Variable, 
         Production = `Generation (TWh)`) %>%
  mutate(across(c(Country, Source), factor))

data$Year <- as.integer(data$Year)

data

Handle Sources

View all Sources

data %>%
  group_by(Source) %>%
  summarise(Total.TWh = sum(Production))

Define Source types

sources <- list(
  fossil = c("Hard Coal", "Lignite", "Gas", "Other fossil"),
  renewable = c("Hydro", "Wind", "Solar", "Bioenergy", "Other renewables"),
  nuclear = c("Nuclear"),
  demand = c("Demand")
)
sources$base <- c(sources$renewable, sources$fossil, sources$nuclear)

Define Source colors

sources$palette <- c("Hard Coal" = "gray10",
                     "Lignite" = "saddlebrown",
                     "Gas" = "darkgoldenrod",
                     "Other fossil" = "darkgray",
                     "Hydro" = "royalblue",
                     "Wind" = "deepskyblue",
                     "Solar" = "gold",
                     "Bioenergy" = "forestgreen",
                     "Other renewables" = "springgreen3",
                     "Nuclear" = "orchid4")

sources$broad.palette <- c("Fossil" = "saddlebrown",
                           "Nuclear" = "orchid4",
                           "Renewables" = "forestgreen")

Add Broad Source

data <- data %>%
  mutate(Broad.Source = factor(case_when(
    Source %in% sources$fossil ~ "Fossil",
    Source %in% sources$nuclear ~ "Nuclear",
    Source %in% sources$renewable ~ "Renewables"
    )))

Filter irrelevant Sources

data <- data %>%
  filter(Source %in% c(sources$base, "Demand"))

Handle Countries

View all Countries

data %>%
  filter(Source == "Demand") %>%
  group_by(Country) %>%
  summarise(Total.Production = sum(Production))

Filter irrelevant Countries

data <- data %>%
  filter(!Country == "EU-27")

Plots

Prepare theme

theme_update(text = element_text(size = 20, color = "gray81"),
             rect = element_rect(fill = "gray14"),
             axis.text = element_text(color = "gray48"),
             panel.background = element_rect(fill = "gray10"),
             panel.grid = element_line(color = "gray15"),
             legend.key = element_rect(fill = "gray14")
             )

theme_set(theme_gray())

Good news

p <- data %>%
  filter(!is.na(Broad.Source)) %>%
  group_by(Year, Broad.Source) %>%
  summarise(Total.Production = sum(Production), .groups = "drop_last") %>%
  ggplot(aes(x = Year, y = Total.Production, color = Broad.Source)) +
  geom_line(size = 2) +
  scale_color_manual(values = sources$broad.palette) +
  theme(legend.position = "bottom") +
  labs(title = "Energy generation sources",
       subtitle = "EU27+1 countries") +
  ylab("Total Generation (TWh)")

p

Static

p

Interactive

ggplotly(p)